User-generated content on the Web increasingly has a geospatial dimension, opening new opportunities and challenges in location-based services and location-based social networks for mining and analyzing user behaviors and patterns. The applications of such analysis range from recommendation systems to geo-marketing. Motivated by these needs, querying and analyzing spatio-textual data has receiv...

Integrating spatio-temporal data as abstract data types into already existing data models is a promising approach to creating spatio-temporal query languages. Based on a formal foundation presented elsewhere, we present the main aspects of an SQL-like, spatio-temporal query language, called STQL. As one of its essential features, STQL allows to query and to retrieve moving objects which describ...

Spatio-temporal databases are a topic of growing research interest but there is still little work reported on spatio-temporal query languages in line with the Object Database Management Group (ODMG) standard. This paper presents the design of such a language, called STOQL, by adding spatial and temporal dimensions to OQL. This language is based upon a data model that extends the ODMG Object Mod...

There is evidence that the mechanisms leading to epileptic seizures can be understood by continuously tracking the ongoing spatio-temporal mappings in the brain. We propose to quantify the spatio-temporal dynamics by using a SOM-based Similarity Index (SI) measure. While it is shown that this measure is statistically as accurate as the original SI measure, it is also computationally faster and ...

An infrastructure is emerging that enables the positioning of populations of on-line, mobile service users. In step with this, research in the management of moving objects has attracted substantial attention. In particular, quite a few proposals now exist for the indexing of moving objects, and more are underway. As a result, there is an increasing need for an independent benchmark for spatio-t...

In this paper, a novel structure is proposed for human activity modeling using time sequential spatio-temporal texture primitives. Gabor filters, which are proven to be robust 2D texture representation tools, are extended to 3D domain to capture spatio-temporal texture features. A well known filtering algorithm and an unsupervised clustering algorithm, the Genetic Chromodynamics, are combined t...

The integrated management of both spatial and temporal components of information is crucial in order to extract significant knowledge from datasets concerning phenomena of interest to a large variety of applications. Moreover, multigranularity, i.e., the capability of representing information at different levels of detail, enhances the data modelling flexibility and improves the analysis of inf...

The increasing complexity of spatio-temporal applications has caused the underlying queries to be more sophisticated and usually carry complex semantics. As a result, the traditional spatio-temporal query types, e.g., range, kNN, and aggregation queries, have become just building blocks in more complex query plans. In this paper, we present the STEPQ system, which is an extensible spatio-tempor...

Spatio-temporal extensions to data models have been an active area of research for a number of years. To date, much of this work has focused on the relational data model, with object data models receiving far less consideration. This paper presents a spatio-historical object model that uses a specialized mechanism, called a history, to maintain knowledge about entities that change over time. Ke...

We propose a framework that learns functional objectcategories from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph that encodes qualitative spatio-temporal patterns of interaction between objects. Event classes are induced by statistical generalization, the instances of which encode similar patterns of spatio-temporal relationships b...